DocumentCode
2504450
Title
Magnetic levitation control based-on neural network and feedback error learning approach
Author
Aliasghary, M. ; Shoorehdeli, M. Aliyari ; Jalilvand, A. ; Teshnehlab, M.
Author_Institution
Istanbul Tech. Univ., Istanbul
fYear
2008
fDate
1-3 Dec. 2008
Firstpage
1426
Lastpage
1430
Abstract
Neural network Based controller is used for controlling a magnetic levitation system. Feedback error learning (FEL) can be regarded as a hybrid control to guarantee stability of control approach. This paper presents simulation of a magnetic levitation system controlled by a FEL neural network and PID controllers. The simulation results demonstrate that this method is more feasible and effective for magnetic levitation system control.
Keywords
magnetic levitation; neurocontrollers; stability; three-term control; PID controllers; feedback error learning approach; magnetic levitation system control; neural network; stability control approach; Adaptive control; Aerodynamics; Coils; Control systems; Error correction; Magnetic levitation; Neural networks; Neurofeedback; Sliding mode control; Three-term control; Feedback error learning; Magnetic levitation system; PID; Sliding mode; neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Power and Energy Conference, 2008. PECon 2008. IEEE 2nd International
Conference_Location
Johor Bahru
Print_ISBN
978-1-4244-2404-7
Electronic_ISBN
978-1-4244-2405-4
Type
conf
DOI
10.1109/PECON.2008.4762702
Filename
4762702
Link To Document